Hot Chips 2026: Applying High Bandwidth Flash (HBF)
High Bandwidth Flash (HBF) is a proposed memory technology designed to provide high-capacity storage with decent bandwidth by integrating flash memory directly onto compute packages. Unlike traditional SSDs, HBF requires specialized software strategies and runtime integration to manage data movement via DMA.
Why it matters
HBF could significantly improve the efficiency of machine learning workloads by bridging the gap between high-speed memory and mass storage.
HBF, or High Bandwidth Flash, uses the same flash memory technology we see in SSDs today. Unlike SSDs, HBF is implemented much like HBM (High Bandwidth Memory). HBF cubes sit on the same package as a compute chip, perhaps even next to HBM. HBF’s idea is to offer much higher capacity than HBM, while still providing decent memory bandwidth. At Hot Chips 2026 tutorials day, Anurag Agarwal and Radhakrishna Giduthuri’s talk explores how HBF could apply to machine learning workloads. No HBF products exist yet, so the talk focuses on simulations, projections, and how software can adapt to take advantage of HBF.
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